Are you ready at ToThePoint?

Building a reinforcement learning simulation of the smart autonomous trash bin.

In another internship we are building a prototype of smart trashcan with necessary sensors to check if it needs to be emptied. When it is time to be emptied it should place itself in a central position for the cleaning personnel to handle.

Description of the assignment

  • The aim of this internship is to build the office in a gaming environment (Unity) and then use reinforcement learning to make the autonomous drive to the central position where the cleaning personnel can pick it up.

Goals

  • The autonomous drive itself should be challenging enough to cope with moving objects and displacement of objects, such as chairs that get in its trajectory or a person walking by.

What you will gain

  • Learn how to design an end-to-end data processing pipeline
  • AND put this in production
  • Gain knowledge about steam processing
  • Gain knowledge and experience in machine learning
  • You will get to know Hadoop
  • You will gain experience in powerful visualization libraries such as D3.js
  • That lovely feeling you get knowing your design will be effectively used in production

What you need

  • You have a shown interest in a challenging but instructive assignment
  • You’d like to explore Machine Learning and stream processing techniques
    • Using Spark, Python or Scala does not scare you at all
    • You know what ReactJS is, or are eager to learn
    • You like to learn about data visualization
    • You like to learn a heck of a lot on a relatively short period of time
Technologies you'll be using
  • Reinforcement learning
  • Unity
  • Tensorflow
  • Python
Location of your assignment

Veldkant 33B, 2550 Kontich

Your mentor

Kevin Smeyers – Technical lead machine learning ToThePoint

ToThePoint logo

Apply for TrashBeat 2.0